Wolfram Science™

Using the basic science of the computational universe to create a new kind of technology

Often known as "NKS" after the title of Stephen Wolfram's 2002 book A New Kind of Science, Wolfram Science is a branch of basic science concerned with understanding the computational universe of possible programs: their behavior, general properties and applications.

Wolfram Science opens up a new way of thinking about computation, and a new approach to creating computational—and other—technology.

Mining the computational universe of possible programs using the ideas of Wolfram Science has become a key approach for creating algorithms used in Wolfram products. And as a company committed to a long-term vision, Wolfram Research continues to support Wolfram Science and its intellectual development.

Simple Programs May Not Do Simple Things

A core discovery in Wolfram Science is that even extremely short programs—say less than a line of Wolfram Language code—can behave in irreducibly rich and complex ways.

Rule 30

Stephen Wolfram's favorite discovery: an incredibly simple program that produces behavior so complex that many aspects of it seem random—and they're random enough to make a great pseudorandom generator.

Exploring the Computational Universe

Like the telescope enabled modern astronomy and led to modern physics, the Wolfram Language and its precursors enabled exploration of the computational universe, and led to Wolfram Science.

The Principle of Computational Equivalence

Stephen Wolfram's central principle, inferred from years of studying the computational universe—with deep implications for science, technology and our ways of thinking about the world.

The Space of All Possible Mathematics

Today's mathematics—as captured in many functions in Mathematica—is based on specific axioms. Wolfram Science highlights the rich space of other possible axioms that yield uninvented branches of mathematics.

Computational Models of Nature

Following extensive work by Stephen Wolfram and many others, simple programs are beginning to overtake mathematical equations as the favored modeling approach for a wide range of systems, especially where complex behavior is seen.

The Threshold of Universality

What does it take to make a universal computer? A key result in Wolfram Science is that even incredibly simple systems can serve as universal computers capable of being programmed to compute anything.

A Paradigm for Biology?

Just as the concept of digital information led us to genomics, so ideas about the computational universe may lead us to an understanding of diverse biological processes—and the complexity that makes medicine difficult.

Hunting for Physics

If simple programs can yield infinitely complex behavior, perhaps our whole universe can be represented as just a simple program. Stephen Wolfram has long explored this idea, generating a rich set of results, but not yet finding our universe...

Automating Creativity

Each program in the computational universe is like a new idea, with its own consequences—that can surprise and amaze us with their unexpectedness, cleverness, usefulness or beauty.

Generalizing the Beauty of Nature

Nature creates complex and beautiful forms by following specific simple programs—but with all the programs in the computational universe, we have an inexhaustible supply of nature-like beauty to explore.

Built in 2005 at the height of the ringtone craze, WolframTones creates short musical pieces by mining them from the computational universe.

The Creativity of Biology

The idea of searching simple programs isn't new: in fact, it's probably a major force in biology, alongside natural selection, that leads to the endlessly creative and complex forms we see in biology.

The Art of Wolfram Science

Simple programs—especially cellular automata—have been widely used to produce decorative art, with forms evoking different styles found by searching the computational universe of programs.

Architectural Form

When an architectural project calls for a form with inner logic but rich and complex structure, it's become common to turn to Wolfram Science to find simple programs that can generate it.

Mining for Algorithms

We've been mining the physical universe for technology for millennia. Now it's time to mine the computational universe—and discover algorithms we'd never imagine. Wolfram Research has been doing it for years.

Building the Wolfram Algorithmbase

An increasing number of Wolfram Language algorithms—for image analysis, function evaluation, randomness generation, machine learning, and much more—were found by mining the computational universe.

The Best Is Often Surprising

Most traditional algorithms have very regular iterative (periodic) or recursive (nested) structures. Wolfram Science searches often yield more optimal algorithms that do not have any such recognizable structure.

The Algorithm Discovery Process

Like drug discovery in the chemical universe, algorithm discovery in the computational universe needs targets—often defined as Wolfram Language programs to compare with or test potential algorithms.

Non-Incremental Engineering

Searching Trillions of Programs

Wolfram Research often searches trillions of programs to find the best algorithm for a particular purpose, typically avoiding incremental and evolutionary methods that tend not to reach the truly unexpected.

Programs We Can't Understand

In the computational universe, it's common to find optimal programs whose operation is at best difficult to understand—necessitating automated methods for assessing performance or proving correctness.

The Secret Sauce of Wolfram|Alpha

Wolfram|Alpha is in many ways the first "killer app" of Wolfram Science—made possible both by the conceptual discoveries of the science, and by the practical methods it introduces.

It's All Just Computation

Stephen Wolfram often credits the Principle of Computational Equivalence for convincing him that computational knowledge doesn't require human-like AI—and that the Wolfram|Alpha project might be doable.

Automated Judgement & Aesthetics

Wolfram|Alpha is full of heuristics that effectively automate human judgment and aesthetic choice. Many of these heuristics were either found or deeply informed by Wolfram Science methods.

Breakthroughs in Language Understanding

The Wolfram|Alpha language understanding system relies heavily on ideas from Wolfram Science, in effect setting up collections of interacting simple programs that represent primitive linguistic processes.

Visualizing Computational Process

Research in Wolfram Science tends to involve extensive visualization of computational processes—a technique widely used in the development of Wolfram|Alpha.

A Foundation for Computation-Related Education

Like mathematics, Wolfram Science provides an introduction to abstract thinking—while also giving students an important theoretical and conceptual foundation for their life in today's world of ubiquitous computation.

Kindergarten On

Following the rules to create a cellular automaton pattern is an activity accessible to kindergartners, already teaching the concept of an algorithm and the importance of precision, and showing connections to the real world.

Accessible Math-Like Thinking

Particularly at lower levels, Wolfram Science teaches the same kind of abstract and rigorous thinking as math—but is often more concrete and accessible, and has immediate surprising connections to the real world.

Computational Lab Notebooks

History & Context

Wolfram Science is an outgrowth of many people's work, with core contributions made since 1980 by Stephen Wolfram—culminating in his 2002 book A New Kind of Science.

Generalizing Science

Since the 1600s, most of exact science has been based on constructing mathematical equations for the world. Wolfram Science is about generalizing this by using programs instead of equations to model the world.

The Science of Complexity

Spawned in some ways by Stephen Wolfram's work in the early 1980s, Complexity Theory studies systems with complex behavior, but doesn't take the same kind of global view of the computational universe as Wolfram Science.

A Classic Paradigm Shift

When Stephen Wolfram's book appeared in 2002, it encountered the same kind of turbulence seen in many historical scientific paradigm shifts, but soon began the long process of widespread acceptance.

More Evidence Comes In

Concepts like the Principle of Computational Equivalence are long-term scientific ideas that require progressive validation—like the 2007 Wolfram-sponsored proof of the simplest universal Turing machine.

Cellular Automata and Beyond

Stephen Wolfram's discoveries in the early 1980s were made in a class of simple programs known as cellular automata. It took his 2002 book to show how broad the discoveries in fact are.

"I Need Mathematica"

Stephen Wolfram started building Mathematica in 1986 so that he could have a tool to continue his work in basic science—and from 1991 to 2002 he used it to make the discoveries in A New Kind of Science.

Tens of Thousands of Academic Papers

Large numbers of academic papers have used Wolfram Science methodologies to create models and make discoveries across an amazing diversity of natural, social and mathematical sciences—and beyond.

The Proof Is In the Results

The ultimate test of a science is whether it's useful—and Wolfram Science has firmly established itself as a major source of scientific, technological, artistic, philosophical and other results.